Jacqui, here is an example that probably does not make any sense but
illustrates what lincom does:
. clear
. webuse nhanes2f
. svyset psuid [pweight=finalwgt], strata(stratid)
pweight: finalwgt
VCE: linearized
Single unit: missing
Strata 1: stratid
SU 1: psuid
FPC 1: <zero>
. svy: mean zinc leadwt
(running mean on estimation sample)
Survey: Mean estimation
Number of strata = 31 Number of obs = 9189
Number of PSUs = 62 Population size = 104176071
Design df = 31
--------------------------------------------------------------
| Linearized
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
zinc | 87.18207 .4944827 86.17356 88.19057
leadwt | 15726.67 340.4806 15032.25 16421.08
--------------------------------------------------------------
. lincom zinc-leadwt
( 1) zinc - leadwt = 0
------------------------------------------------------------------------------
| Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) | -15639.49 340.5765 -45.92 0.000 -16334.1 -14944.88
------------------------------------------------------------------------------
. matlist e(b)
| zinc leadwt
-------------+----------------------
y1 | 87.18207 15726.67
. matlist e(V)
| zinc leadwt
-------------+----------------------
zinc | .2445131
leadwt | -32.53403 115927
. *standard error from covariance matrix
. di sqrt((v[1,1])+(v[2,2])-(2*v[2,1]))
340.57646
. scalar se=sqrt((v[1,1])+(v[2,2])-(2*v[2,1]))
. *t statistic
. di r(estimate)/se
-15639.486
hope this helps, Tim
On Thu, Oct 23, 2008 at 11:18 AM, Bell, Jacqueline S. <[email protected]> wrote:
> Hi
>
> This is a follow-on to a previous message I sent this month asking about how lincom calculates standard errors when clustering is present.
>
> Can anyone advise me on what lincom actually does when estimating differences in parameters from svy:mean or svy:prop?
>
> I have before/after data which is not paired at an individual level, but has a cluster structure. In these circumstances it is not obvious how lincom goes about estimating the before/after difference.
> The two alternatives suggested to me are:
> i) it estimates before and after separately for the whole population, then estimates the difference
> ii)it estimates the difference in each cluster, and then the overall difference.
>
> In the data there are (in most cases) before and after data for each cluster, but often quite severe imbalances in samples before/after within cluster.
>
>
> Thanks for any help, Jacqui
>
>
>
> The University of Aberdeen is a charity registered in Scotland, No SC013683.
>
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